|
@@ -0,0 +1,512 @@
|
|
1
|
+library(ggplot2)
|
|
2
|
+I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)
|
|
3
|
+data = data.frame(I,II,III,IV,V,VI,VII)
|
|
4
|
+ggplot(data) + geom_point()
|
|
5
|
+ggplot(data[I]) + geom_point()
|
|
6
|
+ggplot(data[I],aes(x,y)) + geom_point()
|
|
7
|
+data
|
|
8
|
+mtcars
|
|
9
|
+data = rbind(I,II,III,IV,V,VI,VII)
|
|
10
|
+data
|
|
11
|
+ggplot(data,aes(x="I",y="[],1]")) + geom_point()
|
|
12
|
+plot(data)
|
|
13
|
+par(mfrow=c(3,3))
|
|
14
|
+"indigo"
|
|
15
|
+par(mfrow=c(1,1))
|
|
16
|
+plot(I, color="red",pch=21,xlab = "bins",ylab="frequency")
|
|
17
|
+plot(I, gcolor="red",pch=21,xlab = "bins",ylab="frequency")
|
|
18
|
+plot(I, gcolor="red",pch=21,xlab = "bins",ylab="frequency")
|
|
19
|
+plot(II, gcolor="orange",pch=21,xlab="bins",ylab="frequency")
|
|
20
|
+plot(III, gcolor="yellow",pch=21,xlab="bins",ylab="frequency")
|
|
21
|
+plot(IV, gcolor="green",pch=21,xlab="bins",ylab="frequency")
|
|
22
|
+plot(V, gcolor="blue",pch=21,xlab="bins",ylab="frequency")
|
|
23
|
+plot(VI, gcolor="indigo",pch=21,xlab="bins",ylab="frequency")
|
|
24
|
+plot(VII, gcolor="purple",pch=21,xlab="bins",ylab="frequency")
|
|
25
|
+plot(VII, gcolor="purple",pch=16,xlab="bins",ylab="frequency")
|
|
26
|
+plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")
|
|
27
|
+par(bg="pink")
|
|
28
|
+plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")
|
|
29
|
+points(II, col="orange",pch=16)
|
|
30
|
+plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")
|
|
31
|
+points(II, col="orange",pch=16)
|
|
32
|
+points(III, col="yellow",pch=16)
|
|
33
|
+points(IV, col="green",pch=16)
|
|
34
|
+points(V, col="blue",pch=16)
|
|
35
|
+points(VI, col="indigo",pch=16)
|
|
36
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
37
|
+points(II, col="orange",pch=8)
|
|
38
|
+points(III, col="yellow",pch=8)
|
|
39
|
+points(IV, col="green",pch=8)
|
|
40
|
+points(V, col="blue",pch=8)
|
|
41
|
+points(VI, col="indigo",pch=8)
|
|
42
|
+points(VII, col="purple",pch=8)
|
|
43
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
44
|
+points(II, col="orange",pch=8)
|
|
45
|
+points(III, col="yellow",pch=8)
|
|
46
|
+points(IV, col="green",pch=8)
|
|
47
|
+points(V, col="blue",pch=8)
|
|
48
|
+points(VI, col="indigo",pch=8)
|
|
49
|
+legend(0,0,legend=c("I","II","III","IV","V","VI","VII")
|
|
50
|
+)
|
|
51
|
+legend(0,0,legend=c("I","II","III","IV","V","VI","VII"))
|
|
52
|
+legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))
|
|
53
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
54
|
+points(II, col="orange",pch=8)
|
|
55
|
+points(III, col="yellow",pch=8)
|
|
56
|
+points(IV, col="green",pch=8)
|
|
57
|
+points(V, col="blue",pch=8)
|
|
58
|
+points(VI, col="purple",pch=8)
|
|
59
|
+points(VII, col="black",pch=8)
|
|
60
|
+legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))
|
|
61
|
+legend(0,1,legend=c("I","II","III","IV","V","VI","VII"))
|
|
62
|
+legend(1,95,legend=c("I","II","III","IV","V","VI","VII"))
|
|
63
|
+legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))
|
|
64
|
+legend(1,1,legend=c("I","II","III","IV","V","VI","VII"),fill="white")
|
|
65
|
+legend(1,1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
66
|
+legend(legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
67
|
+legend(0,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
68
|
+legend(3,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
69
|
+legend(x=0,y=1legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
70
|
+legend(x=0,y=1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
71
|
+par(bg="pink")
|
|
72
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
73
|
+points(II, col="orange",pch=8)
|
|
74
|
+points(III, col="yellow",pch=8)
|
|
75
|
+points(IV, col="green",pch=8)
|
|
76
|
+points(V, col="blue",pch=8)
|
|
77
|
+points(VI, col="purple",pch=8)
|
|
78
|
+points(VII, col="black",pch=8)
|
|
79
|
+legend(x=0,y=1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
80
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))
|
|
81
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))
|
|
82
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=1:7)
|
|
83
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
84
|
+points(II, col="orange",pch=8)
|
|
85
|
+points(III, col="yellow",pch=8)
|
|
86
|
+points(IV, col="green",pch=8)
|
|
87
|
+points(V, col="blue",pch=8)
|
|
88
|
+points(VI, col="purple",pch=8)
|
|
89
|
+points(VII, col="black",pch=8)
|
|
90
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=1:7)
|
|
91
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))
|
|
92
|
+plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")
|
|
93
|
+points(II, col="orange",pch=8)
|
|
94
|
+points(III, col="yellow",pch=8)
|
|
95
|
+points(IV, col="green",pch=8)
|
|
96
|
+points(V, col="blue",pch=8)
|
|
97
|
+points(VI, col="purple",pch=8)
|
|
98
|
+points(VII, col="black",pch=8)
|
|
99
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))
|
|
100
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))
|
|
101
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill=c("red","orange","yellow","green","blue","purple","black"))
|
|
102
|
+plot(I, col="red",pch=8,xlab = "Bins",ylab="Frequency")
|
|
103
|
+points(II, col="orange",pch=8)
|
|
104
|
+points(III, col="yellow",pch=8)
|
|
105
|
+points(IV, col="green",pch=8)
|
|
106
|
+points(V, col="blue",pch=8)
|
|
107
|
+points(VI, col="purple",pch=8)
|
|
108
|
+points(VII, col="black",pch=8)
|
|
109
|
+legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill=c("red","orange","yellow","green","blue","purple","black"))
|
|
110
|
+bins = rep(c(1:31),each=7)
|
|
111
|
+bins
|
|
112
|
+1:31
|
|
113
|
+bins = rep(c((1:31)),each=7)
|
|
114
|
+1:31
|
|
115
|
+bins
|
|
116
|
+bins = rep(c((1:31)),times=7)
|
|
117
|
+bins
|
|
118
|
+sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)
|
|
119
|
+sample
|
|
120
|
+library(tidyverse)
|
|
121
|
+I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)
|
|
122
|
+II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)
|
|
123
|
+III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)
|
|
124
|
+IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)
|
|
125
|
+V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)
|
|
126
|
+install.packages("assertthat")
|
|
127
|
+library(tidyverse)
|
|
128
|
+install.packages("Rcpp")
|
|
129
|
+library(tidyverse)
|
|
130
|
+I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)
|
|
131
|
+II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)
|
|
132
|
+III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)
|
|
133
|
+IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)
|
|
134
|
+V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)
|
|
135
|
+VI = c(0,0,0,.002,0,.007,.005,.009,.009,.011,.014,.018,.043,.016,.027,.018,.043,.080,.062,.050,.084,.082,.062,.071,.050,.082,.057,.043,.005,.014,.034)
|
|
136
|
+VII = c(0,.002,.002,.003,.002,.003,.013,.013,.018,.015,.020,.016,.031,.010,.042,.016,.021,.028,.056,.056,.090,.044,.044,.056,.065,.075,.083,.075,.025,.026,.051)
|
|
137
|
+bins = rep(c((1:31)),times=7)
|
|
138
|
+sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)
|
|
139
|
+values = c(I,II,III,IV,V,VI,VII)
|
|
140
|
+length(values)
|
|
141
|
+length(bins)
|
|
142
|
+length(sample)
|
|
143
|
+data = data.frame(bins,sample,values)
|
|
144
|
+data
|
|
145
|
+ggplot(data) +
|
|
146
|
+geom_point(mapping=aes(x=bins,y=values,color=sample)) +
|
|
147
|
+theme_bw()
|
|
148
|
+ggplot(data) +
|
|
149
|
+geom_point(mapping=aes(x=bins,y=values,color=sample)) +
|
|
150
|
+theme_bw() + xlab("Bin") + ylab("Alelles") +
|
|
151
|
+scale_x_continuous(breaks=(1:31))
|
|
152
|
+library(tidyverse)
|
|
153
|
+ggplot(data) +
|
|
154
|
+geom_point(mapping=aes(x=bins,y=values,color=sample)) +
|
|
155
|
+theme_bw() + xlab("Bin") + ylab("Alelle Frecuency") +
|
|
156
|
+scale_x_continuous(breaks=(1:31))
|
|
157
|
+a = c(9.96,9.97,9.95)
|
|
158
|
+sd(a)
|
|
159
|
+b = sd(a)
|
|
160
|
+b
|
|
161
|
+help(sd)
|
|
162
|
+a = c(10.01,10.26,9.96)
|
|
163
|
+sd(a)
|
|
164
|
+a = c(9.63,9.74,9.76)
|
|
165
|
+sd(a)
|
|
166
|
+a = c(7.24,7.59,8.46)
|
|
167
|
+sd(a)
|
|
168
|
+a = c(1.027,1.029,1.026)
|
|
169
|
+sd(a)
|
|
170
|
+mean(a)
|
|
171
|
+2,5/10.27
|
|
172
|
+2.5/10.27
|
|
173
|
+10.25/10
|
|
174
|
+density = c(0.99,1.006,1.027,1.045,1.067)
|
|
175
|
+concentration = (0.87,2.01,5.02,7.00,10.00)
|
|
176
|
+concentration = c(0.87,2.01,5.02,7.00,10.00)
|
|
177
|
+plot(density, concentration)
|
|
178
|
+library(tidyverse)
|
|
179
|
+I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)
|
|
180
|
+II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)
|
|
181
|
+III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)
|
|
182
|
+IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)
|
|
183
|
+V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)
|
|
184
|
+VI = c(0,0,0,.002,0,.007,.005,.009,.009,.011,.014,.018,.043,.016,.027,.018,.043,.080,.062,.050,.084,.082,.062,.071,.050,.082,.057,.043,.005,.014,.034)
|
|
185
|
+VII = c(0,.002,.002,.003,.002,.003,.013,.013,.018,.015,.020,.016,.031,.010,.042,.016,.021,.028,.056,.056,.090,.044,.044,.056,.065,.075,.083,.075,.025,.026,.051)
|
|
186
|
+bins = rep(c((1:31)),times=7)
|
|
187
|
+sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)
|
|
188
|
+values = c(I,II,III,IV,V,VI,VII)
|
|
189
|
+data = data.frame(bins,sample,values)
|
|
190
|
+ggplot(data) +
|
|
191
|
+geom_point(mapping=aes(x=bins,y=values,color=sample)) +
|
|
192
|
+theme_bw() + xlab("Bin") + ylab("Alelle Frecuency") +
|
|
193
|
+scale_x_continuous(breaks=(1:31))
|
|
194
|
+library(tidyverse)
|
|
195
|
+density = c(0.99,1.006,1.027,1.045,1.067)
|
|
196
|
+concentration = c(0.87,2.01,5.02,7.00,10.00)
|
|
197
|
+data = data.frame(density,concentration)
|
|
198
|
+data
|
|
199
|
+ggplot(data) +
|
|
200
|
+geom_point(mapping=aes(x=density,y=concentration,color=sample)) +
|
|
201
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")
|
|
202
|
+ggplot(data) +
|
|
203
|
+geom_point(mapping=aes(x=density,y=concentration)) +
|
|
204
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")
|
|
205
|
+ggplot(data) +
|
|
206
|
+geom_point(mapping=aes(x=density,y=concentration)) +
|
|
207
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")+
|
|
208
|
+geom_smooth(method='lm')
|
|
209
|
+ggplot(data) +
|
|
210
|
+geom_point(mapping=aes(x=density,y=concentration)) +
|
|
211
|
+geom_smooth(method='lm') +
|
|
212
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")
|
|
213
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
214
|
+geom_point() +
|
|
215
|
+geom_smooth(method='lm') +
|
|
216
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")
|
|
217
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
218
|
+geom_point() +
|
|
219
|
+geom_smooth(method='lm') +
|
|
220
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +
|
|
221
|
+ggtitle("Density vs Concentration of Prepared Solutions")
|
|
222
|
+data = data.frame(density,concentration)
|
|
223
|
+model <- lm(concentration~density, data=data)
|
|
224
|
+summary(model)
|
|
225
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
226
|
+geom_point() +
|
|
227
|
+geom_smooth(method='lm') +
|
|
228
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +
|
|
229
|
+ggtitle("Density vs Concentration of Prepared Solutions") +
|
|
230
|
+geom_label(x = x_lab, y = y_lab, label = "avg rate")
|
|
231
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
232
|
+geom_point() +
|
|
233
|
+geom_smooth(method='lm') +
|
|
234
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +
|
|
235
|
+ggtitle("Density vs Concentration of Prepared Solutions") +
|
|
236
|
+geom_label(x = 1, y = 5, label = "avg rate")
|
|
237
|
+summary(model)
|
|
238
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
239
|
+geom_point() +
|
|
240
|
+geom_smooth(method='lm') +
|
|
241
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +
|
|
242
|
+ggtitle("Density vs Concentration of Prepared Solutions") +
|
|
243
|
+geom_label(x = 1, y = 5, label = "y = 120.94x - 119.23") +
|
|
244
|
+geom_label(x = 1, y = 4, label = "R-squared: 0.9931") +
|
|
245
|
+xx
|
|
246
|
+library(tidyverse)
|
|
247
|
+density = c(0.99,1.006,1.027,1.045,1.067)
|
|
248
|
+concentration = c(0.87,2.01,5.02,7.00,10.00)
|
|
249
|
+data = data.frame(density,concentration)
|
|
250
|
+model <- lm(concentration~density, data=data)
|
|
251
|
+summary(model)
|
|
252
|
+ggplot(data, aes(x=density,y=concentration)) +
|
|
253
|
+geom_point() +
|
|
254
|
+geom_smooth(method='lm') +
|
|
255
|
+theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +
|
|
256
|
+ggtitle("Density vs Concentration of Prepared Solutions") +
|
|
257
|
+geom_label(x = 1, y = 5, label = "y = 120.94x - 119.23") +
|
|
258
|
+geom_label(x = 1, y = 4, label = "R-squared: 0.9931")
|
|
259
|
+p = c(5.10,5.25,5.16)
|
|
260
|
+v = c(4.86,5.01,4.94)
|
|
261
|
+mean(p)
|
|
262
|
+sd(p)
|
|
263
|
+mean(v)
|
|
264
|
+sd(v)
|
|
265
|
+A = c(0.335,0.199,0.0953,0.0278)
|
|
266
|
+concentration = c(0.60,0.30,0.12,0.06)
|
|
267
|
+data = data.frame(A,concentration)
|
|
268
|
+model <- lm(A~concentration, data=data)
|
|
269
|
+summary(model)
|
|
270
|
+data = data.frame(A,concentration)
|
|
271
|
+model <- lm((A-0.01674)~(concentration-0.01674), data=data)
|
|
272
|
+summary(model)
|
|
273
|
+data = data.frame(A,concentration)
|
|
274
|
+model <- lm((A-0.01674)~(concentration-0.01674), data=data)
|
|
275
|
+summary(model)
|
|
276
|
+data = data.frame(A,concentration)
|
|
277
|
+model <- lm(I(A-0.01674)~(concentration-0.01674), data=data)
|
|
278
|
+summary(model)
|
|
279
|
+c = c(5.10,5.26,5.17)
|
|
280
|
+sd(c)
|
|
281
|
+mean(c)
|
|
282
|
+library(tidycensus)
|
|
283
|
+library(tidyverse)
|
|
284
|
+install.package("tidycensus")
|
|
285
|
+install.packages("tidycensus")
|
|
286
|
+library(tidyverse)
|
|
287
|
+library(tidycensus)
|
|
288
|
+library(tidycensus)
|
|
289
|
+library(tidyverse)
|
|
290
|
+library("writexl")
|
|
291
|
+census_api_key("7a853acf81fd5758228680556ac831138c40b83e")
|
|
292
|
+variables = load_variables(2019,"acs5")
|
|
293
|
+variables
|
|
294
|
+variables$name
|
|
295
|
+match("DP02",variables)
|
|
296
|
+variables$name[2000]
|
|
297
|
+variables$name[3000]
|
|
298
|
+variables$name[5000]
|
|
299
|
+variables$name[10000]
|
|
300
|
+variables$name[600000]
|
|
301
|
+variables$name[60000]
|
|
302
|
+variables$name[50000]
|
|
303
|
+variables$name[40000]
|
|
304
|
+variables$name[30000]
|
|
305
|
+variables$name[20000]
|
|
306
|
+variables = load_variables(2019,"acs5/profile")
|
|
307
|
+variables
|
|
308
|
+View(variables)
|
|
309
|
+length(variables)
|
|
310
|
+length(variables[1])
|
|
311
|
+variables = load_variables(2021,"acs5/profile")
|
|
312
|
+variables = load_variables(2020,"pl/profile")
|
|
313
|
+variables = load_variables(2020,"acs5/profile")
|
|
314
|
+variables
|
|
315
|
+View(variables)
|
|
316
|
+test = get_acs(geography = "county",
|
|
317
|
+state = "PR",
|
|
318
|
+year = 2020,
|
|
319
|
+variables = "DP02_0001")
|
|
320
|
+test
|
|
321
|
+View(test)
|
|
322
|
+test = get_acs(geography = "region",
|
|
323
|
+state = "PR",
|
|
324
|
+year = 2020,
|
|
325
|
+variables = "DP02_0001")
|
|
326
|
+test = get_acs(geography = "block",
|
|
327
|
+state = "PR",
|
|
328
|
+year = 2020,
|
|
329
|
+variables = "DP02_0001")
|
|
330
|
+test = get_acs(geography = "county",
|
|
331
|
+state = "PR",
|
|
332
|
+year = 2020,
|
|
333
|
+variables = "DP02_0001")
|
|
334
|
+View(test)
|
|
335
|
+variables$name
|
|
336
|
+codes = variables$name
|
|
337
|
+test = get_acs(geography = "county",
|
|
338
|
+state = "PR",
|
|
339
|
+year = 2020,
|
|
340
|
+variables = codes)
|
|
341
|
+view(test)
|
|
342
|
+noNA = na.omit(test)
|
|
343
|
+noNA
|
|
344
|
+view(noNA)
|
|
345
|
+view(variables)
|
|
346
|
+DP02table = noNA %>% filter(startsWith(variable,"DP02"))
|
|
347
|
+DP02table
|
|
348
|
+view(DP02table)
|
|
349
|
+DP02table = noNA %>% filter(startsWith(variable,"DP02"))
|
|
350
|
+DP03table = noNA %>% filter(startsWith(variable,"DP03"))
|
|
351
|
+DP04table = noNA %>% filter(startsWith(variable,"DP04"))
|
|
352
|
+DP05table = noNA %>% filter(startsWith(variable,"DP05"))
|
|
353
|
+view(DP04table)
|
|
354
|
+variables$name
|
|
355
|
+variables$label
|
|
356
|
+noNA$GEOID
|
|
357
|
+table(noNA$GEOID)
|
|
358
|
+length(table(noNA$GEOID))
|
|
359
|
+view(test)
|
|
360
|
+#amount of GEOIDS
|
|
361
|
+for (x in 1:78){
|
|
362
|
+labelCol = c(labelCol, labels)
|
|
363
|
+}
|
|
364
|
+#add label column
|
|
365
|
+#create empty vector
|
|
366
|
+labelCol = c()
|
|
367
|
+#amount of GEOIDS
|
|
368
|
+for (x in 1:78){
|
|
369
|
+labelCol = c(labelCol, labels)
|
|
370
|
+}
|
|
371
|
+#combine test and cols
|
|
372
|
+test["label"] = labelCol
|
|
373
|
+labelCol
|
|
374
|
+#amount of GEOIDS
|
|
375
|
+for (x in 1:78){
|
|
376
|
+labelCol = c(labelCol, labels)
|
|
377
|
+}
|
|
378
|
+labels()
|
|
379
|
+labels()
|
|
380
|
+labels
|
|
381
|
+variables
|
|
382
|
+variables$label
|
|
383
|
+label
|
|
384
|
+labels
|
|
385
|
+label0 = variables$label
|
|
386
|
+label0
|
|
387
|
+#add label column
|
|
388
|
+#create empty vector
|
|
389
|
+labelCol = c()
|
|
390
|
+#amount of GEOIDS
|
|
391
|
+for (x in 1:78){
|
|
392
|
+labelCol = c(labelCol, label0)
|
|
393
|
+}
|
|
394
|
+#combine test and cols
|
|
395
|
+test["label"] = labelCol
|
|
396
|
+view(test)
|
|
397
|
+#omit NA rows
|
|
398
|
+noNA = na.omit(test)
|
|
399
|
+DP02table = noNA %>% filter(startsWith(variable,"DP02"))
|
|
400
|
+DP03table = noNA %>% filter(startsWith(variable,"DP03"))
|
|
401
|
+DP04table = noNA %>% filter(startsWith(variable,"DP04"))
|
|
402
|
+DP05table = noNA %>% filter(startsWith(variable,"DP05"))
|
|
403
|
+view(DP02table)
|
|
404
|
+GEOIDS = table(test$GEOID)
|
|
405
|
+GEOIDS
|
|
406
|
+#rearrange cols
|
|
407
|
+test = test[c("NAME","label","variable","estimate","moe","GEOID")]
|
|
408
|
+view(test)
|
|
409
|
+pnorm(1.25)
|
|
410
|
+pnorm(1.25) - pnorm(-1.25)
|
|
411
|
+pnorm(1.875) - pnorm(-1.25)
|
|
412
|
+pnorm(0.75) - pnorm(-1.25)
|
|
413
|
+pnorm(1.25) - pnorm(-2.5)
|
|
414
|
+pnorm(2.7) - pnorm(2)
|
|
415
|
+pnorm(1.54)
|
|
416
|
+pnorm(1.54) - pnorm(-1.54)
|
|
417
|
+qnorm(0.4564)
|
|
418
|
+qnorm(0.9564)
|
|
419
|
+qnorm(0.05)
|
|
420
|
+qnorm(0.07)
|
|
421
|
+qnorm(0.94)
|
|
422
|
+qnorm(0.43)
|
|
423
|
+pnorm(-0.18)
|
|
424
|
+qnorm(0.43)
|
|
425
|
+pnorm(-0.17)
|
|
426
|
+pnorm(-1.30)
|
|
427
|
+qnorm(0.70,400,80)
|
|
428
|
+(106 - qnorm(0.70,106,21))/21
|
|
429
|
+(qnorm(0.70,106,21)-106)/21
|
|
430
|
+(qnorm(0.87,106,28)
|
|
431
|
+)
|
|
432
|
+qnorm(0.77)
|
|
433
|
+0.74 * 17 + 108
|
|
434
|
+pnorm(252,369,59)
|
|
435
|
+pnorm(140,120,18) - pnorm(110,120,18)
|
|
436
|
+qnorm(0.87,100,10)
|
|
437
|
+1- pnorm(96,100,20)
|
|
438
|
+pnorm(180,159,10) - pnorm(150,159,10)
|
|
439
|
+(pnorm(180,159,10) - pnorm(150,159,10))*425
|
|
440
|
+x = c(-40,0,260,460,960)
|
|
441
|
+px = c(0.99510,1/200,1/500,1/1000,1/2000)
|
|
442
|
+len(px)
|
|
443
|
+length(px)
|
|
444
|
+Ex = sum(x*px)
|
|
445
|
+Vx = sum(((x-Ex)^2)*px)
|
|
446
|
+Ex
|
|
447
|
+Vx
|
|
448
|
+library(tidycensus)
|
|
449
|
+library(tidyverse)
|
|
450
|
+tableYear = 2020
|
|
451
|
+#log on with API
|
|
452
|
+census_api_key("7a853acf81fd5758228680556ac831138c40b83e")
|
|
453
|
+#load variables
|
|
454
|
+pueblos = 78
|
|
455
|
+variables = load_variables(2020,"acs5/profile")
|
|
456
|
+codes = variables$name
|
|
457
|
+codess
|
|
458
|
+codes
|
|
459
|
+startsWith(codes,"DP02")
|
|
460
|
+callData = function(year,table,municipality) {
|
|
461
|
+#year is between 2000 and 2020
|
|
462
|
+#table is dp02pr, dp03, dp04, dp05
|
|
463
|
+#load variables
|
|
464
|
+variables = load_variables(year,"acs5/profile")
|
|
465
|
+#load variable vectors
|
|
466
|
+codes = variables$name
|
|
467
|
+codesBool = startsWith(codes,table)
|
|
468
|
+codes = codes[codesBool]
|
|
469
|
+labels = variables$label[codesBool]
|
|
470
|
+#pull table
|
|
471
|
+bigTable = get_acs(geography = "county",
|
|
472
|
+state = "PR",
|
|
473
|
+year = year,
|
|
474
|
+county = municipality,
|
|
475
|
+variables = codes)
|
|
476
|
+bigTable$Label = labels
|
|
477
|
+return(bigTable)
|
|
478
|
+}
|
|
479
|
+table = callData(2020,"DP05","Aguada")
|
|
480
|
+table
|
|
481
|
+view(table)
|
|
482
|
+view(table)
|
|
483
|
+callData = function(year,table,municipality) {
|
|
484
|
+#year is between 2000 and 2020
|
|
485
|
+#table is dp02pr, dp03, dp04, dp05
|
|
486
|
+#load variables
|
|
487
|
+variables = load_variables(year,"acs5/profile")
|
|
488
|
+#load variable vectors
|
|
489
|
+codes = variables$name
|
|
490
|
+codesBool = startsWith(codes,table)
|
|
491
|
+codes = codes[codesBool]
|
|
492
|
+labels = variables$label[codesBool]
|
|
493
|
+#pull table
|
|
494
|
+bigTable = get_acs(geography = "county",
|
|
495
|
+state = "PR",
|
|
496
|
+year = year,
|
|
497
|
+county = municipality,
|
|
498
|
+variables = codes)
|
|
499
|
+bigTable$Label = labels
|
|
500
|
+bigTable = bigTable[c("Label","estimate","moe")]
|
|
501
|
+return(bigTable)
|
|
502
|
+}
|
|
503
|
+table = callData(2020,"DP05","Aguada")
|
|
504
|
+view(table)
|
|
505
|
+plumber::plumb(file='C:/Users/kashi/Desktop/R.R')$run()
|
|
506
|
+plumb(file='C:/Users/kashi/Desktop/R.R')$run()
|
|
507
|
+setwd("C:/Users/kashi/Desktop")
|
|
508
|
+plumb(file='R.R')$run()
|
|
509
|
+setwd("C:/Users/kashi/Desktop/censusproject")
|
|
510
|
+plumb(file='R.R')$run()
|
|
511
|
+plumb(file='R.R')$run()
|
|
512
|
+plumb(file='R.R')$run()
|